agentic/code/addons/aiwg-utils/skills/checkpoint/SKILL.md
Create, list, or recover mid-workflow checkpoints so interrupted work resumes from a known-good position
npx skillsauth add jmagly/aiwg checkpointInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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You create, list, or recover lightweight mid-workflow checkpoints that allow a crashed or interrupted workflow to continue from a known-good position rather than restart from scratch.
Alternate expressions and non-obvious activations (primary phrases are matched automatically from the skill description):
| Pattern | Example | Action |
|---------|---------|--------|
| Create (named) | "checkpoint this as iteration-3-complete" | Run aiwg checkpoint create --name iteration-3-complete |
| Create (anonymous) | "create a checkpoint" | Run aiwg checkpoint create |
| List | "show available checkpoints" | Run aiwg checkpoint list |
| Recover (latest) | "recover from the last checkpoint" | Run aiwg checkpoint recover |
| Recover (specific) | "recover checkpoint ckpt_7b2f1a" | Run aiwg checkpoint recover ckpt_7b2f1a |
When triggered:
Extract intent:
create, list, or recover?Run the appropriate subcommand:
# Create — anonymous
aiwg checkpoint create
# Create — named
aiwg checkpoint create --name <name>
# List all checkpoints
aiwg checkpoint list
# Recover — most recent checkpoint
aiwg checkpoint recover
# Recover — specific checkpoint by ID or name
aiwg checkpoint recover <id>
Checkpoints vs. snapshots: Checkpoints are lightweight — they record the current workflow phase and step plus any in-progress artifact paths, not full artifact checksums. Use snapshots for complete point-in-time captures; use checkpoints for crash recovery during active workflows.
| | Checkpoint | Snapshot | |---|---|---| | Purpose | Crash recovery | Reproducibility | | Size | Small (phase + step + artifact refs) | Full (versions + checksums) | | Created by | Manual or agent loop (auto) | Manual only | | Use for | Resume interrupted run | Replay from known state |
Automatic creation: Agent loops create checkpoints automatically between iterations. Manual create supplements this for critical workflow milestones.
Storage: Checkpoints are stored in .aiwg/checkpoints/ as lightweight JSON files.
Report the result — on create, confirm the checkpoint ID and position; on recover, confirm which step the workflow will resume from.
User: "Create a checkpoint after iteration 3 completes"
Extraction: Create subcommand, name iteration-3-complete
Action:
aiwg checkpoint create --name iteration-3-complete
Response: "Checkpoint iteration-3-complete created (ID: ckpt_7b2f1a). Recorded position: Construction phase, iteration 3, step 12/15. In-progress artifacts: .aiwg/working/tests/integration-plan-draft.md. Stored at .aiwg/checkpoints/ckpt_7b2f1a.json."
User: "What checkpoints do we have?"
Extraction: List subcommand
Action:
aiwg checkpoint list
Response:
ID Name Date Phase / Step
ckpt_3a8c12 (auto) 2026-03-28 10:04:51 Construction / iter 1, step 8
ckpt_9f20de (auto) 2026-03-29 14:17:33 Construction / iter 2, step 15
ckpt_7b2f1a iteration-3-complete 2026-03-30 09:55:02 Construction / iter 3, step 12
User: "The workflow crashed — recover from the last checkpoint"
Extraction: Recover subcommand, use most recent
Action:
aiwg checkpoint recover
Response: "Recovering from most recent checkpoint iteration-3-complete (ckpt_7b2f1a). Resuming Construction phase, iteration 3, step 12/15. In-progress artifact .aiwg/working/tests/integration-plan-draft.md reloaded. Ready to continue."
User: "Recover from checkpoint ckpt_9f20de"
Extraction: Recover subcommand, ID ckpt_9f20de
Action:
aiwg checkpoint recover ckpt_9f20de
Response: "Recovering from checkpoint ckpt_9f20de (auto, 2026-03-29 14:17:33). Resuming Construction phase, iteration 2, step 15/15. No in-progress artifacts. Ready to continue from this position."
If the user's intent is ambiguous:
aiwg checkpoint list to see what's available."data-ai
Report which research-corpus radar sidecars are overdue for refresh. Computes staleness (days since last refresh vs the cadence window) for every radar, sorted most-overdue-first. Runs via `aiwg corpus radar-status`.
data-ai
Aggregate research-corpus radar sidecars into a corpus or per-cluster freshness report — totals, overdue count, per-cluster / per-GRADE / per-trajectory breakdowns, an overdue table, and per-radar rationale snippets. Runs via `aiwg corpus radar-report`.
testing
Scaffold radar/freshness sidecars for research-corpus REFs. Pulls title/authors from the citation sidecar and GRADE from the analysis doc, defaults the refresh cadence from GRADE and the cluster from a corpus-local map, and stamps documentation/radar/REF-XXX-radar.md. Runs via `aiwg corpus radar-init`.
data-ai
Compute an entity's publication trajectory — per-year paper counts, topic drift, hot-streak detection (≥3 consecutive A-grade years), and career phase. Runs via `aiwg corpus profile-temporal`.